Released: Dec 6, 2023

Mises à jour de 2023.3

Fonctionnalités

AI Assistant [General Availability]

• AI Assistant is out of preview - JetBrains AI Assistant is now generally available with a number of new and improved features to increase your productivity in JetBrains IDEs.
• Get insights about your DataFrame with JetBrains AI Assistant - The Explain code feature now offers an effortless way to gain insights into your DataFrame. Once activated, AI Assistant will receive essential information about your dataset, such as column names and descriptive statistics. This enables the assistant to provide relevant details about and analysis of your DataFrame. Furthermore, you have the option to explore more in-depth analysis by engaging in a prolonged dialogue with the assistant.
• You can use AI Assistant in DataSpell as a supplemental feature with a JetBrains AI Service subscription.

dbt

• Introducing dbt Core support
  • DataSpell now provides support for dbt Core, a modern data transformation framework. dbt Core simplifies the data transformation process and encourages best engineering practices in data analysis, such as modularization, testing, and documentation. It is particularly user-friendly for individuals already familiar with SQL. Here are several benefits of using dbt Core in DataSpell:
    • Streamlined project initiation: You can effortlessly initiate your dbt project by utilizing a preconfigured template.
    • Simplified run, build, and debug processes: Execute, build, or debug your project with ease using Run Configurations.
    • Intelligent code completion: DataSpell offers intelligent code completion for both SQL and YML files.

SQL and Python

• SQL cells - DataSpell has significantly enhanced the connection between SQL and Python by introducing SQL cells. Similar to Python or Markdown cells, SQL cells are now available for use in your Jupyter notebooks.
• Full Line code completion - DataSpell's advanced code completion has been further enhanced to provide a more tailored experience. You can now take advantage of code completion that is customized for your current file, thanks to a local model integrated directly within the IDE. This model learns from your code, allowing it to suggest entire lines of code and thereby improving the efficiency and effectiveness of your data analysis workflows.
• Other databases and SQL plugin improvements
  • Materialized views in Redshift are now introspected and displayed in a dedicated node in the Database Explorer.
  • Introduced DynamoDB support.

Interactive tables

• In-table statistics - Simplified access to descriptive statistics for a dataframe can help data professionals significantly boost their efficiency. In DataSpell, this process has been made more user-friendly. You can now easily access essential data insights, such as missing values, mean, standard deviation, and more, directly in the table header. This functionality is available in both Jupyter notebooks and Python scripts, supporting both pandas and Polars. Additionally, you can effortlessly identify the data type of each column by glancing at the icons in the table's header.
• Categorical data distribution statistics - When dealing with categorical data, you can have easy access to viewing distribution in interactive tables. This feature allows you to quickly observe a list of the most frequently occurring values, along with their respective percentages. In cases with numerous unique values, you can easily access the total count of these distinct entries within the column.
• Data distribution histograms in tables - A data distribution histogram is an essential tool in data analysis, providing a visual snapshot of data distribution, as well as aiding in pattern recognition, outlier detection, and data quality assessment. In DataSpell, you can now easily access these histograms directly in table headers. These histograms are accessible in the default compact mode and also in the detailed view.
• Simplifying data visualization in tables - To streamline your data analysis workflow, a new easy graph builder has been introduced. This new feature streamlines the creation of graphs from your table data, enabling quick and effortless data visualization.
• AI Assistant in tables - You can now access valuable DataFrame insights by clicking the AI Assistant icon in the top right corner of your interactive tables. The assistant provides instant information, and you can engage in further analysis by continuing the conversation.

UI and navigation

• Hide main toolbar - Added an option to hide the main toolbar when using the IDE's default viewing mode, just like in the old UI. To declutter your workspace and remove the toolbar, select Appearance and uncheck the Toolbar option.
• Improved navigation - To enhance your navigation experience when working with a variety of file types in the editor at the same time, default color-coded highlighting has been introduced for editor tabs, mirroring their appearance in the Project tool window.
• Speed Search - The Speed Search functionality, which allows you to quickly navigate within tool windows and dialogs, is now available via a shortcut.